Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Convert content between platforms (blog to Twitter thread, article to LinkedIn post, etc.). Optimize for each platform's format, tone, and best practices. Use when user wants to adapt content for different social media platforms.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Transform content across platforms with platform-specific optimization.
Activate when the user:
Analyze Source Content
Optimize for Twitter/X
Optimize for LinkedIn
Optimize for Instagram
Optimize for Facebook
Optimize for TikTok (if applicable)
# Content Repurposing: [Original Title]
## Source Summary
**Original Format**: [Blog post/Article/Video]
**Key Message**: [One sentence]
**Target Audience**: [Description]
---
## Twitter/X Thread (10 tweets)
**Tweet 1/10** (Hook)
[Attention-grabbing opening tweet]
**Tweet 2/10**
[First key point]
**Tweet 3/10**
[Second key point]
[Continue through full thread...]
**Tweet 10/10**
[Summary and CTA]
---
## LinkedIn Post
[Hook paragraph with strong opening]
[Main content with strategic line breaks]
Key takeaways:
• [Point 1]
• [Point 2]
• [Point 3]
[Closing thought or question]
**Hashtags**: #Industry #Topic #Relevant
---
## Instagram Caption
[Strong hook line]
[Concise main message - 3-4 short paragraphs with emojis]
[Call to action]
.
.
.
#hashtag1 #hashtag2 #hashtag3 #hashtag4 #hashtag5
[continue to 15-20 relevant hashtags]
**Visual Suggestion**: [Description of ideal image/carousel]
---
## Facebook Post
[Conversational opening]
[Brief, engaging content]
[Question to drive comments]
#Hashtag
---
## TikTok Script (if applicable)
**Hook (0-3 sec)**: [Attention grabber]
**Main Content (3-45 sec)**: [Key points delivered quickly]
**CTA (45-60 sec)**: [Call to action]
**On-Screen Text Ideas**:
- [Text 1]
- [Text 2]
**Audio Suggestion**: [Trending sound or style]
**Hashtags**: #FYP #topic #niche
---
## Analytics Recommendations
- Best posting times: [Platform-specific suggestions]
- Engagement tactics: [Specific strategies per platform]
- A/B testing ideas: [Variations to test]
User: "Turn this blog post into social media content" Response: Extract key points → Create Twitter thread with hook → Write LinkedIn post with professional tone → Generate Instagram caption with hashtags → Provide Facebook version → Include posting strategy
User: "I need to repurpose this podcast episode for social" Response: Summarize key moments → Create quotable tweets → Write LinkedIn article-style post → Generate audiogram caption for Instagram → Suggest TikTok clips → Provide hashtag research
User: "Convert this case study into a Twitter thread" Response: Identify success story arc → Create compelling thread hook → Break down into 8-10 tweet structure → Add data points strategically → End with CTA → Suggest accompanying visuals
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
日本語の概要は準備中です。原文の説明を表示しています。
Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
日本語の概要は準備中です。原文の説明を表示しています。
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
日本語の概要は準備中です。原文の説明を表示しています。
Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.
日本語の概要は準備中です。原文の説明を表示しています。
Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.
日本語の概要は準備中です。原文の説明を表示しています。